Abstract
Two methods of ranking $K$ samples for rank tests comparing $K$ populations are considered. The first method ranks the $K$ samples jointly; the second ranks the $K$ samples pairwise. These procedures were first suggested by Dunn (1964), and Steel (1960), respectively. It is shown that both ranking procedures are asymptotically equivalent for rank-sum tests satisfying certain nonrestrictive conditions. The problem is formulated in terms of multiple comparisons, but is applicable to other nonparametric procedures based on $K$-sample rank statistics.
Citation
James A. Koziol. Nancy Reid. "On the Asymptotic Equivalence of Two Ranking Methods for $K$-Sample Linear Rank Statistics." Ann. Statist. 5 (6) 1099 - 1106, November, 1977. https://doi.org/10.1214/aos/1176343998
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